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This research applies denoising diffusion probabilistic models and Bayesian optimization to solve a critical stability challenge in robotic disassembly by generating shared fixture layouts that adapt as components are removed. The study validates its physics-informed approach through extensive load testing on irregular products like screwdrivers and shavers, demonstrating that unified planning significantly improves operational feasibility without requiring reconfiguration.
Planning a Shared Modular Fixture Layout Across Robotic Disassembly Stages
arXiv:2608.27151v1 Announce Type: new Abstract: Stable support remains challenging in robotic disassembly of irregularly shaped products. As components are progressively removed, the available support surfaces, mass distribution, and task loads change throughout the process. A fixture layout designed for one workpiece state may therefore become infeasible at later stages, motivating unified support planning over the complete disassembly sequence. This paper presents a modular vacuum-based fixturing system that plans one shared support configuration for the complete disassembly sequence of a screwdriver or shaver, allowing each sequence to proceed without fixture reconfiguration. To search the mixed continuous--discrete layout space under repeated cross-stage evaluation, a denoising diffusion probabilistic model generates physics-informed initial configurations that are refined through Bayesian optimization. Robotic screw and component-removal experiments verified the disassembly feasibility of the planned layouts, while 11 directional-load tests quantified their stability. Comparisons between the measured operational loads and directional responses yielded mean empirical stability margins of 66.9% for the screwdriver and 81.6% for the shaver. These results demonstrate that a product-specific shared layout can provide stable support throughout the tested robotic disassembly sequence.
Abstract:Stable support remains challenging in robotic disassembly of irregularly shaped products. As components are progressively removed, the available support surfaces, mass distribution, and task loads change throughout the process. A fixture layout designed for one workpiece state may therefore become infeasible at later stages, motivating unified support planning over the complete disassembly sequence. This paper presents a modular vacuum-based fixturing system that plans one shared support configuration for the complete disassembly sequence of a screwdriver or shaver, allowing each sequence to proceed without fixture reconfiguration. To search the mixed continuous--discrete layout space under repeated cross-stage evaluation, a denoising diffusion probabilistic model generates physics-informed initial configurations that are refined through Bayesian optimization. Robotic screw and component-removal experiments verified the disassembly feasibility of the planned layouts, while 11 directional-load tests quantified their stability. Comparisons between the measured operational loads and directional responses yielded mean empirical stability margins of 66.9% for the screwdriver and 81.6% for the shaver. These results demonstrate that a product-specific shared layout can provide stable support throughout the tested robotic disassembly sequence.
15 pages, 9 figures. Submitted to IEEE Transactions on Automation Science and Engineering (T-ASE)
Robotics (cs.RO)
arXiv:2608.27151 [cs.RO]
(or arXiv:2608.27151v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.27151 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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